Commit 4e45d987 authored by Oleg Dzhimiev's avatar Oleg Dzhimiev
Browse files

cleanup

parent e35a9afe

array.cu

+1 −1
Original line number Diff line number Diff line
@@ -70,7 +70,7 @@ int myCreateCUDAArray(uint8_t *tf_ptr){ 


    // check if the GPU did the same as the CPU

    bool workedCorrectly = true;

    printf("CUDA kernel incrementing test:\n");

    printf("CUDA kernel simple incrementing test:\n");

    for(int i=0;i<numberOfNumbers;i++)

    {

        if (numbers1[i] != numbers2[i])

main.cpp

+41 −37
Original line number Diff line number Diff line
@@ -32,27 +32,19 @@ using tensorflow::Status; 
using tensorflow::Tensor;





Status loadGraph(unique_ptr<tensorflow::Session> *session){

Status createGraphAndSession(unique_ptr<tensorflow::Session> *session){



    tensorflow::GraphDef graph_def;



    using namespace tensorflow;

    using namespace tensorflow::ops;



    auto scope = Scope::NewRootScope();



    // TF likes power of 2

    tensorflow::TensorShape shape = tensorflow::TensorShape({256});



    auto a  = Placeholder(scope.WithOpName("array_tensor_in"), DT_UINT8, Placeholder::Shape(shape));



    //auto c0 = Const(scope,{256});

    //auto c1 = Const(scope, (uint8_t)1, {});

    //auto c2  = Fill(scope, c0, c1);



    auto b  = Identity(scope.WithOpName("array_tensor_out"), a);

    //auto b  = Identity(scope.WithOpName("array_tensor_out"), c2);

    //auto b = Add(scope.WithOpName("array_tensor_out"),c2,a);

    auto a  = ops::Placeholder(scope.WithOpName("array_tensor_in"), DT_UINT8, ops::Placeholder::Shape(shape));

    auto b  = ops::Identity(scope.WithOpName("array_tensor_out"), a);



    TF_CHECK_OK(scope.ToGraphDef(&graph_def));
@@ -65,7 +57,7 @@ Status loadGraph(unique_ptr<tensorflow::Session> *session){ 
    session->reset(tensorflow::NewSession(session_options));

    Status session_create_status = (*session)->Create(graph_def);

    if (!session_create_status.ok()){

        LOG(ERROR) << "loadGraph(): ERROR" << session_create_status;

        LOG(ERROR) << "createGraphAndSession(): ERROR" << session_create_status;

    }

    return Status::OK();

}
@@ -109,7 +101,7 @@ int main(int, char**) { 
        LOG(INFO) << "Tensorflow built with CUDA, keep running" << endl;

    }



    // check and init CUDA drivers and libs

    // check and init CUDA drivers and libs?

    void *hHandleDriver = nullptr;

    CUresult cuda_res = cuInit(0, __CUDA_API_VERSION, hHandleDriver);

    if (cuda_res != CUDA_SUCCESS)
@@ -123,14 +115,17 @@ int main(int, char**) { 
    }

    LOG(INFO) << "\033[1;32m" << "CUDA init: ok" << "\033[0m";





    // construct graph and create TF session

    std::unique_ptr<tensorflow::Session> session;

    createGraphAndSession(&session);



    loadGraph(&session);



    // do the opts and allocate tensor in GPU

    // NOTE: must match with graph names

    const string inputLayer  = "array_tensor_in:0";

    const string outputLayer = "array_tensor_out:0";



    // do the opts

    CallableOptions opts;

    Session::CallableHandle feed_gpu_fetch_cpu;
@@ -150,7 +145,6 @@ int main(int, char**) { 


    // TF likes power of 2 and 256s

    tensorflow::TensorShape shape = tensorflow::TensorShape({256});

    // allocate tensor on the GPU

    tensorflow::PlatformGpuId platform_gpu_id(0);



    tensorflow::GPUMemAllocator *sub_allocator =
@@ -165,23 +159,32 @@ int main(int, char**) { 


    LOG(INFO) << "\033[1;37m" << "Is CUDA Tensor? " << (IsCUDATensor(inputTensor)?"\033[1;32myes":"\033[1;31mno") << "\033[0m";



    // pointer to tensor data

    tensorflow::uint8 *p = inputTensor.flat<tensorflow::uint8>().data();



    // run and check

    vector<Tensor> outputs;



    for(int i=0;i<2;i++){



        cout << endl;



        if (i==0){

            LOG(INFO) << "\033[1;32m" << "RunCallable()... No feeding (zeroes)" << "\033[0m";

        }

        if (i==1){

            LOG(INFO) << "\033[1;32m" << "RunCallable()... Feeding from CUDA kernel"<< "\033[0m";

            // CUDA kernel call

            // NOTE: do not allocate memory for p inside the kernel

            myCreateCUDAArray(p);



    vector<Tensor> outputs;

    LOG(INFO) << "RunCallable()...";

        }



        runStatus = session->RunCallable(feed_gpu_fetch_cpu, {inputTensor}, &outputs, nullptr);

    if (!runStatus.ok())

    {

        if (!runStatus.ok()){

            LOG(ERROR) << "Running model failed: " << runStatus;

            return -1;

        }



        LOG(INFO) << "RunCallable() output:";



        LOG(INFO) << outputs[0].DebugString();

        auto tmap = outputs[0].tensor<uint8_t, 1>();
@@ -191,6 +194,7 @@ int main(int, char**) { 
            if (d!=255) cout << ", ";

        }

        cout << "\033[0m" << endl;

    }



    session->ReleaseCallable(feed_gpu_fetch_cpu);